docs: def chebyshev(h1, h2): # 12 us @array, 36 us @list \w 100 bins
      r"""
      Chebyshev distance.
      
      Also Tchebychev distance, Maximum or :math:`L_{\infty}` metric; equal to Minowski
      distance with :math:`p=+\infty`. For the case of :math:`p=-\infty`, use `chebyshev_neg`.
      
      The Chebyshev distance between two histograms :math:`H` and :math:`H'` of size :math:`m` is
      defined as:
      
      .. math::
      
          d_{\infty}(H, H') = \max_{m=1}^M|H_m-H'_m|
      
      *Attributes:*
      
      - semimetric (triangle equation satisfied?)
      
      *Attributes for normalized histograms:*
      
      - :math:`d(H, H')\in[0, 1]`
      - :math:`d(H, H) = 0`
      - :math:`d(H, H') = d(H', H)`
      
      *Attributes for not-normalized histograms:*
      
      - :math:`d(H, H')\in[0, \infty)`
      - :math:`d(H, H) = 0`
      - :math:`d(H, H') = d(H', H)`
      
      *Attributes for not-equal histograms:*
      
      - not applicable
      
      Parameters
      ----------
      h1 : sequence
          The first histogram.
      h2 : sequence
          The second histogram.
      
      Returns
      -------
      chebyshev : float
          Chebyshev distance.
      
      See also
      --------
      minowski, chebyshev_neg
      """
      h1, h2 = __prepare_histogram(h1, h2)
      return max(scipy.absolute(h1 - h2))